When asked, most spinal cords injured (SCI) patients suffering tetraplegia report that regaining the ability to use their hands would be more important than any other lost function. Functional Electrical Stimulation (FES) is a remarkable technology that can be used to cause the muscles of a paralyzed patient to contract. FES has been used to restore grasping to paralyzed patients. The primary limitations of FES for the restoration of dexterous hand movements are the inability to activate muscles with adequate force and specificity, and the inadequacy of the control signals that the paralyzed patient can generate. The Brain Machine Interface (BMI) may provide the necessary control signal. BMIs have reached the forefront of the neural engineering endeavor to treat patients suffering from paralysis. Yet despite remarkable BMI technology advances, virtually all current applications are limited to daily, several-hour sessions in a single, constrained setting. Current BMIs that restore movement do so only through a robot or limb exoskeleton, and none provides explicit control of force. These constraints will ultimately limit patients' ability to adapt fully to the technology, to use it readily at any time of the day or night, and to apply it to a broad range of behaviors. By coupling BMI technology to FES, we believe we can overcome these limitations. We have demonstrated a unique BMI using a peripheral nerve block to paralyze a monkey's hand as a model for SCI: We use information about intended muscle activity extracted from cortical recordings to produce an FES control signals that allows the monkeys to regain voluntary control of their wrist and hand. We propose to use this BMI-controlled FES model to restore round-the-clock hand use to monkey subjects for month-long periods of time. We will develop adaptive, state-dependent decoders designed to broaden the range of motor behaviors for which the FES BMI will be useful. We will improve both the quality of information we can obtain from the brain and the effectiveness with which we can activate muscles by using new types of electrodes for neural recording and peripheral nerve stimulation. Finally, we will develop a long-lasting peripheral nerve block to cause month-long paralysis. We will record telemetrically, to control a fully implanted neuromuscular stimulator that will allow us an unprecedented opportunity to study long-term adaptation to a BMI neuroprosthesis. We will study the behavioral improvement that results from this adaptation both in the monkey's natural home-cage behaviors and in the more constrained lab setting. We will study the interaction between the monkey's adaptation and the adaptive algorithms. This work will provide important basic information about the adaptive capability of the adult, mammalian brain, the extent to which BMI exposure can rescue cortex that undergoes maladaptive changes in response to paralysis, and the extent to which long- term practice improves BMI performance.